Abstract
Voice biometrics is widely adopted for identity authentication in mobile devices. However, voice authentication is vulnerable to spoofing attacks, where an adversary may deceive the voice authentication system with pre-recorded or synthesized samples from the legitimate user or by impersonating the speaking style of the targeted user. In this paper, we design and implement VoicePop, a robust software-only anti-spoofing system on smartphones. VoicePop leverages the pop noise, which is produced by the user breathing while speaking close to the microphone. The pop noise is delicate and subject to user diversity, making it hard to record by replay attacks beyond a certain distance and to imitate precisely by impersonators. We design a novel pop noise detection scheme to pinpoint pop noises at the phonemic level, based on which we establish individually unique relationship between phonemes and pop noises to identify legitimate users and defend against spoofing attacks. Our experimental results with 18 participants and three types of smartphones show that VoicePop achieves over 93.5% detection accuracy at around 5.4% equal error rate. VoicePop requires no additional hardware but only the built-in microphones in virtually all smartphones, which can be readily integrated in existing voice authentication systems for mobile devices.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.